The present disclosure generally relates to optical analysis tools and, more specifically, to optical analysis tools having an integrated computational element that can be reconfigured for analyzing a characteristic of a sample.
Spectroscopic analyses are well known for their versatility for detecting a wide variety of substances by obtaining and analyzing a spectrum. Most spectroscopic instruments are general purpose and are not configured to detect any one particular substance or class of substance. Accordingly, involved and time-consuming spectral processing and/or sample preparation operations may be needed to analyze for a particular substance within a given sample to obtain a satisfactory spectrum, especially when multiple detectable substances are present. Although spectroscopic analyses can often be routinely carried out under regulated laboratory conditions, they can be considerably more difficult to transition into less controlled environments, such as the oilfield and other process settings, where operational conditions may damage and/or limit the accuracy of conventional spectroscopic equipment and techniques.
Optical computing devices represent a distinct alternative to conventional spectroscopic equipment and techniques. As used herein, the term “optical computing device” will refer to an optical analysis tool configured to receive an input of electromagnetic radiation from a sample and produce an output of electromagnetic radiation from a processing element that is diagnostic of a characteristic of the sample. Optical computing devices utilize an integrated computational element (ICE), also referred to as an “ICE core,” which is a processing element that is specifically designed to analyze for a given component or characteristic of interest in a sample upon optical interaction of electromagnetic radiation therewith. In analyzing for the characteristic, a spectrum is not produced by the optical computing device. Instead, the integrated computational element determines a dot product for the regression vector of the characteristic, as discussed in further detail below.
As used herein, the term “characteristic” will refer to a substance's concentration in a sample or a derived physical property for the sample. The transmission or reflection function of an integrated computational element may represent the regression vector for a characteristic of interest, and the transmission or reflection function may be weighted with respect to wavelength by taking the dot product of the regression vector over the wavelength space being analyzed. Accordingly, upon optically interacting electromagnetic radiation with a sample and with an integrated computational element, the electromagnetic radiation may change in a known and specific way that may be representative of the characteristic's magnitude in the sample. Following receipt of the electromagnetic radiation at a detector and calculation of the dot product, a numerical output from the detector can be correlated to the characteristic of interest. Even though a complex mixture of substances may be present in a given sample, an integrated computational element may be able to distinguish and analyze for a particular substance or characteristic based upon the unique regression vector represented by the integrated computational element.
Optical computing devices may be advantageous compared to conventional spectroscopic techniques, since analyses may be conducted rapidly, often in real-time, with limited to no sample preparation involved. Rather than obtaining an optical spectrum as in conventional spectroscopic techniques, which may require further interpretation and deconvolution to take place for analyzing a characteristic, the numerical output produced by optical computing devices may be directly correlated to a characteristic of interest. Optical computing devices are also much more rugged than conventional spectroscopic equipment and can be deployed in locales where spectroscopic analyses may otherwise be problematic. Accordingly, optical computing devices may often be desirable for analyzing complex mixtures in various process environments, such as those encountered in the oilfield industry.
Optical computing analyses may utilize a single integrated computational element or, more commonly, a plurality of integrated computational elements. A plurality of integrated computational elements may be used to analyze for multiple characteristics of a sample or a single sample characteristic. Using multiple integrated computational elements to analyze for a single sample characteristic may involve optically interacting electromagnetic radiation with the sample and with multiple integrated computational elements in sequence or by computationally combining the numerical outputs of two or more integrated computational elements with one another. Benefits that may be realized when utilizing multiple integrated computational elements in the analysis of a single characteristic of interest include, but are not limited to, increased analytical sensitivity, signal normalization and combinations thereof.
Conventionally, integrated computational elements refer to optical processing elements containing a plurality of optical thin film layers formed from various materials whose indices of refraction and thicknesses may vary between each layer. Oftentimes, conventional integrated computational elements may contain a plurality of alternating layers of materials having high and low indices of refraction such that the layer compositions, thicknesses, and ordering may be chosen, based upon calculations, to selectively transmit or reflect predetermined fractions of electromagnetic radiation at different wavelengths. In doing so, the integrated computational element essentially may function as an interference filter, and the integrated computational element may substantially mimic the regression vector corresponding to a particular characteristic of interest in a sample. Taking the dot product of the regression vector allows the characteristic to be determined.
Although conventional integrated computational elements may have exceptional utility in a variety of analyses, they are not without their limitations. Although design calculations and thin-layer deposition techniques for producing conventional integrated computational elements are well understood, they can be time-consuming and expensive to carry out, and there is no guarantee that a given integrated computational element will sufficiently mimic a regression vector as intended upon testing and/or deployment. Since the regression vectors for various sample characteristics generally differ, multiple integrated computational elements may need to be designed and tested for analyzing multiple characteristics. Furthermore, when the regression vector for a given sample characteristic is complex, the calculations and layer deposition pattern for the integrated computational element may be correspondingly complex. Finally, conventional integrated computational elements often function most effectively in mimicking a sample characteristic's regression vector in the near-infrared region of the electromagnetic spectrum, and it can often be difficult to modify the design of the integrated computational element to extend the working wavelength range into other spectral regions, such as the mid- and far-infrared and ultraviolet regions.
Another potential limitation associated with conventional integrated computational elements involves the deployment of multiple integrated computational elements in an optical analysis tool. Multiple integrated computational elements may be disposed along an extended optical pathway or upon a movable assembly that allows different integrated computational elements to be exposed to electromagnetic radiation in the optical pathway at various points in time (e.g., through lateral or rotational motion of the movable assembly). Either configuration, however, can result in a profile that is too bulky to fit effectively within confined operating locales. Extreme operating environments can also be taxing toward mechanical operating mechanisms used to produce lateral or rotational motion in such instances, not to mention possible footprint and reliability issues associated with the mechanical operating mechanism itself. Furthermore, it can be problematic in some deployment locales, such as within a subterranean wellbore, to supply sustained operating power for producing ongoing lateral or rotational motion.